Summary
✨ AI‑Generated
A hands-on forward-deployed AI engineering role in a rapidly growing financial-services environment. You will identify high-value use cases with business stakeholders and take solutions from discovery to production, building LLM-powered agents, RAG pipelines, document intelligence, and workflow automation. The work involves integrating established enterprise systems with newer AI-native platforms and modern data infrastructure.
Highlights
Hands-on AI engineering with direct exposure to business leaders and opportunities to take AI solutions from initial discovery through production. The role spans lending, operations, risk, customer service, and integration challenges, with practical work on LLM agents, RAG, document intelligence, workflow automation, and modern data platforms.
Description
Want to build AI that actually ships? Work directly with the CTO and Head of Technology?
Our client is an established (non-big4), Australian bank that's growing fast, both by winning new customers and by buying smaller competitors.
Each acquisition brings new systems, data and customers, which makes this one of the most interesting places in Australian banking to build practical AI.
The role
This is a hands-on, forward-deployed engineering role.
You'll sit close to the business, find where AI can make a real difference, and take solutions from first conversation to live production.
What you'll do
Find and scope high-value AI use cases across lending, operations, risk, customer service and acquisition integration.Build and deploy LLM-powered solutions, such as agents, RAG pipelines (AI that answers from the bank's own documents and data), document intelligence and workflow automation.Integrate across traditional core banking and newer AI-native platforms.Build on Snowflake in a multi-cloud AWS and Azure environment.Prototype fast, prove value, then harden solutions for a regulated bank.Advise senior stakeholders and help shape a growing AI engineering capability.
What you'll bring
Strong software engineering skills, with Python essential.LLM or machine learning solutions deployed into production, not just proofs of concept.Hands-on Snowflake experience, plus AWS and/or Azure.Comfort integrating with legacy and enterprise systems.A consulting-style, forward-deployed mindset: you're confident with stakeholders and focused on outcomes.An understanding of regulated environments, with financial services experience strongly preferred.
Nice to have: LangChain, LlamaIndex or Semantic Kernel, Amazon Bedrock, Azure OpenAI or Snowflake Cortex, and experience with M&A integration or core banking modernisation.
Why this role
You'll work directly with the CTO and Head of Technology, with no layers in between.You'll have real, visible impact at a bank that's growing and investing in AI.You'll work across a varied mix of legacy and cutting-edge technology.
Interested? Apply here or message me for a confidential chat.
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